The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7–13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activ- ity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific con- tributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field

Alpha-band rhythms in visual task performance: phase-locking by rhythmic sensory stimulation

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8-12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles

The duration of a co-occurring sound modulates visual detection performance in humans.

The duration of sounds can affect the perceived duration of co-occurring visual stimuli. However, it is unclear whether this is limited to amodal processes of duration perception or affects other non-temporal qualities of visual perception

Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach

Accurate outcome detection in neuro-rehabilitative settings is crucial for appropriate long-term rehabilitative decisions in patients with disorders of consciousness (DoC). EEG measures derived from high-density EEG can provide helpful information regarding diagnosis and recovery in DoC patients. However, the accuracy rate of EEG biomarkers to predict the clinical outcome in DoC patients is largely unknown. This study investigated the accuracy of psychophysiological biomarkers based on clinical EEG in predicting clinical outcomes in DoC patients. To this aim, we extracted a set of EEG biomarkers in 33 DoC patients with traumatic and nontraumatic etiologies and estimated their accuracy to discriminate patients' etiologies and predict clinical outcomes 6 months after the injury. Machine learning reached an accuracy of 83.3% (sensitivity = 92.3%, specificity = 60%) with EEG-based functional connectivity predicting clinical outcome in nontraumatic patients. Furthermore, the combination of functional connectivity and dominant frequency in EEG activity best predicted clinical outcomes in traumatic patients with an accuracy of 80% (sensitivity = 85.7%, specificity = 71.4%). These results highlight the importance of functional connectivity in predicting recovery in DoC patients. Moreover, this study shows the high translational value of EEG biomarkers both in terms of feasibility and accuracy for the assessment of DoC

Polygenic Susceptibility to Papillary Thyroid Cancer in Italian Subjects.

olygenic Susceptibility to Papillary Thyroid Cancer in Italian Subjects INTRODUCTION AND AIM. Thyroid cancer is the most common endocrine neoplasia, with an estimated age- standardized incidence rate of 6.7 per 100000 worldwide in 2018 [1]. This rate is rapidly increasing and papillary thy- roid carcinoma (PTC) is the main histotype. PTC suscepti- bility is the result of genetic predisposition, environmental factors and lifestyle. We studied the genetic combination that characterizes PTC affected subjects, differentiating them from healthy controls. METHODS AND RESULTS. We considered the genetic variants (SNPs) significantly associated with PTC on the PubMed database. 184 informative SNPs were selected, considering linkage disequilibrium. Then, SNPs data were extracted from the online 1000 Genomes database,comprising genome of 2504 unselected individuals col- lected worldwide. The combination of 184 SNPs associ- ated with PTC was used to group individuals in different risk-clusters according to their genetic structure, calcu- lated by Bayesian statistics, as previously performed for polycystic ovary syndrome [2]. Individuals were distrib- uted among 7 groups worldwide, indicating different de- gree of genetic predisposition to PTC. We then considered genetic data from about 1200 individuals (697 PTC versus 497 healthy controls) of Central/South Italian origin reg- istered in a GWAS, specific for PTC [3]. This first analysis was refined using the 33 SNPs reasonably most causa- tive of genetic clustering (26 with p<0.05 at trend test in GWAS and 7 with p<0.05 in the model of recessive inher- itance). At multivariate logistic regression analysis, PTC and healthy controls resulted genetically different (ODDS RATIO 188.6, 95%CI 64.35-552.8), revealing diverse pre- disposition to develop cancer. Afterwards, these results have been confirmed in an independent cohort of Italian subjects (234 PTC and 100 controls). Then, the genetic structure of each subject was indicated as a percentage of affinity to each risk-cluster and re-analyzed together with other risk factors: sex, body-mass index, area of origin and familiarity (quantified in a growing score as the degree of kinship increases). These data were analyzed together by principal component analysis and clustering of the two groups was even more pronounced. The most contributive factors to the diversity between PTC and healthy controls were genetics and familiarity. CONCLUSION. We demonstrated that PTC affected subjects are genetically different from healthy controls, and that the difference is identifiable in a peculiar combi- nation of genetic variants

Cracking the code of oscillatory activity

Neural oscillations are ubiquitous measurements of cognitive processes and dynamic routing and gating of information. The fundamental and so far unresolved problem for neuroscience remains to understand how oscillatory activity in the brain codes information for human cognition. In a biologically relevant cognitive task, we instructed six human observers to categorize facial expressions of emotion while we measured the observers' EEG. We combined state-of-the-art stimulus control with statistical information theory analysis to quantify how the three parameters of oscillations (i.e., power, phase, and frequency) code the visual information relevant for behavior in a cognitive task. We make three points: First, we demonstrate that phase codes considerably more information (2.4 times) relating to the cognitive task than power. Second, we show that the conjunction of power and phase coding reflects detailed visual features relevant for behavioral response-that is, features of facial expressions predicted by behavior. Third, we demonstrate, in analogy to communication technology, that oscillatory frequencies in the brain multiplex the coding of visual features, increasing coding capacity. Together, our findings about the fundamental coding properties of neural oscillations will redirect the research agenda in neuroscience by establishing the differential role of frequency, phase, and amplitude in coding behaviorally relevant information in the brai

The speed of parietal theta frequency drives visuospatial working memory capacity

The speed of theta brain oscillatory activity is thought to play a key role in determining working memory (WM) capacity. Individual differences in the length of a theta cycle (ranging between 4 and 7 Hz) might determine how many gamma cycles (>30 Hz) can be nested into a theta wave. Gamma cycles are thought to represent single memory items; therefore, this interplay could determine individual memory capacity. We directly tested this hypothesis by means of parietal transcranial alternating current stimulation (tACS) set at slower (4 Hz) and faster (7 Hz) theta frequencies during a visuospatial WM paradigm. Accordingly, we found that 4-Hz tACS enhanced WM capacity, while 7-Hz tACS reduced WM capacity. Notably, these effects were found only for items presented to the hemifield contralateral to the stimulation site. This provides causal evidence for a frequency-dependent and spatially specific organization of WM storage, supporting the theta–gamma phase coupling theory of WM capacity

Event-related alpha suppression in response to facial motion

This article has been made available through the Brunel Open Access Publishing Fund.While biological motion refers to both face and body movements, little is known about the visual perception of facial motion. We therefore examined alpha wave suppression as a reduction in power is thought to reflect visual activity, in addition to attentional reorienting and memory processes. Nineteen neurologically healthy adults were tested on their ability to discriminate between successive facial motion captures. These animations exhibited both rigid and non-rigid facial motion, as well as speech expressions. The structural and surface appearance of these facial animations did not differ, thus participants decisions were based solely on differences in facial movements. Upright, orientation-inverted and luminance-inverted facial stimuli were compared. At occipital and parieto-occipital regions, upright facial motion evoked a transient increase in alpha which was then followed by a significant reduction. This finding is discussed in terms of neural efficiency, gating mechanisms and neural synchronization. Moreover, there was no difference in the amount of alpha suppression evoked by each facial stimulus at occipital regions, suggesting early visual processing remains unaffected by manipulation paradigms. However, upright facial motion evoked greater suppression at parieto-occipital sites, and did so in the shortest latency. Increased activity within this region may reflect higher attentional reorienting to natural facial motion but also involvement of areas associated with the visual control of body effectors. © 2014 Girges et al

A chronometric exploration of high-resolution ‘sensitive TMS masking’ effects on subjective and objective measures of vision

Transcranial magnetic stimulation (TMS) can induce masking by interfering with ongoing neural activity in early visual cortex. Previous work has explored the chronometry of occipital involvement in vision by using single pulses of TMS with high temporal resolution. However, conventionally TMS intensities have been high and the only measure used to evaluate masking was objective in nature. Recent studies have begun to incorporate subjective measures of vision, alongside objective ones. The current study goes beyond previous work in two regards. First, we explored both objective vision (an orientation discrimination task) and subjective vision (a stimulus visibility rating on a four-point scale), across a wide range of time windows with high temporal resolution. Second, we used a very sensitive TMS-masking paradigm: stimulation was at relatively low TMS intensities, with a figure-8 coil, and the small stimulus was difficult to discriminate already at baseline level. We hypothesized that this should increase the effective temporal resolution of our paradigm. Perhaps for this reason, we are able to report a rather interesting masking curve. Within the classical-masking time window, previously reported to encompass broad SOAs anywhere between 60 and 120 ms, we report not one, but at least two dips in objective performance, with no masking in-between. The subjective measure of vision did not mirror this pattern. These preliminary data from our exploratory design suggest that, with sensitive TMS masking, we might be able to reveal visual processes in early visual cortex previously unreported

The COGs (context, object, and goals) in multisensory processing

Our understanding of how perception operates in real-world environments has been substantially advanced by studying both multisensory processes and “top-down” control processes influencing sensory processing via activity from higher-order brain areas, such as attention, memory, and expectations. As the two topics have been traditionally studied separately, the mechanisms orchestrating real-world multisensory processing remain unclear. Past work has revealed that the observer’s goals gate the influence of many multisensory processes on brain and behavioural responses, whereas some other multisensory processes might occur independently of these goals. Consequently, other forms of top-down control beyond goal dependence are necessary to explain the full range of multisensory effects currently reported at the brain and the cognitive level. These forms of control include sensitivity to stimulus context as well as the detection of matches (or lack thereof) between a multisensory stimulus and categorical attributes of naturalistic objects (e.g. tools, animals). In this review we discuss and integrate the existing findings that demonstrate the importance of such goal-, object- and context-based top-down control over multisensory processing. We then put forward a few principles emerging from this literature review with respect to the mechanisms underlying multisensory processing and discuss their possible broader implications